1. Field of the Invention
The present invention relates to an appearance inspection method and system of a heat exchanger, more particularly relates to an appearance inspection method and system of a fin-and-tube type heat exchanger used in automotive heaters and the like.
2. Description of the Related Art
FIG. 1 is a perspective view showing a fin-and-tube type heat exchanger 10 generally used in automotive heaters and the like. FIG. 2 is an enlarged view of the fin and tube parts wherein the heat exchanger 10 of FIG. 1 is rotated 90 degrees. The heat exchanger 10 is provided with a core 11 serving as a heat exchanger part. The core 11 is provided with a plurality of tubes 12 through which a fluid serving as a heat exchange medium passes and a large number of fins 13 that are attached to the surfaces of the tubes to increase the heat transfer area. Reference numerals 14 indicate tank parts and 15 side plates.
The core 11 of the fin-and-tube type heat exchanger 10 is formed by a plurality of unit elements, each provided with one straight tube 12 and a fin 13 attached in a bellows-like state on its surface, regularly repeated and connected. In such a unit element, the fin 13 is comprised of a flat sheet folded into an S-shape which is repeated to form a bellows shape. The fin 13 is therefore a folded part provided with a plurality of curved parts (fin R parts). Defects in the tubes 12 and fins 13 of such a heat exchanger can be detected by appearance inspection with a considerable success rate. Such appearance inspection has been improved for automation, labor-saving, and raising accuracy up to now. Recently, inspection methods making use of image processing have been introduced.
As such an inspection method using image processing, the inspection method such as shown in Japanese Unexamined Patent Publication (A) No. 2005-321300 is known.
This inspection method is an appearance inspection method of a core of a heat exchanger having a repeated pattern of the two components of a tube and fin. According to this inspection method, two images are captured in order to apply a fault detection method using image processing. One of the images of the part being inspected is an image captured as a tube inspection image while controlling the illumination so that the brightness of the image of the fin part is suppressed. The other inspection image is captured as a fin inspection image by an illumination by which the fin part can be inspected.
Further, a two-dimensional Fourier transform is applied to these tube or fin inspection images to obtain inspection images at the spatial frequency domains. Next, for example, parts of the input images are utilized to prepare mask image data for samples of good parts and this data is used to remove the frequency components of the good parts from the inspection images. Then, a two-dimensional inverse Fourier transform is further applied to obtain fault detection images.
However, when using the aforementioned prior art for inspecting tubes, the following problems have occurred. That is, in order to extract a tube, it was necessary to capture two inspection images at illuminations suitable for the tubes or the fins. When obtaining a tube inspection image, the image is captured while adjusting the level of the brightness until the fins are no longer visible, so differences in the surface conditions of a workpiece have become a cause of detection errors in inspection.
In tube inspection, transformed images of the inspection images obtained by application of a fast Fourier transform (FFT) and the transformed images of a normal tube part of the inspection image are used to find defects, so unless all of the tubes are at equal pitches, good precision detection is not possible. Further, by applying an FFT to the entire core, factors leading to detection errors will occur and the amount of data will end up becoming massive. In the case of FFT analysis, the transforms have to be applied twice, for regular and inverse, or else defects cannot be detected, thus causing the processing speed to drop. When performing inspection processing using FFT analysis, judgment based on the dimensional threshold value was difficult.
FIG. 3 is a view showing examples of tube defects.
As modes of defects of the tubes, there are dents, deformed bends, deposits of dirt/foreign matter, etc. A “dent” is a defect resulting from a tube being struck and indented. As examples of the dents, there are cases where the indented part is sharp in angle and the width center of a tube is greatly indented. A dent where the center of a tube is greatly indented is displayed on the image as a black mark. A “deformed bend” is a defect in which the tube width greatly changes due to a deformed bend. A “deposit of dirt/foreign matter” on a tube is a dirt/foreign matter deposit defect and is displayed on the image as a black mark. Up until now, these defects could not be identified.